Publication Details

Note: HTML Version at
http://www.ai.sri.com/~wilkins/papers/jair-2003/

Abstract

There is an increasing need for automated support for humans monitoring the
activity of distributed teams of cooperating agents, both human and machine.
We characterize the domain-independent challenges posed by this problem, and
describe how properties of domains influence the challenges and their solutions.
We will concentrate on dynamic, data-rich domains where humans are ultimately
responsible for team behavior. Thus, the automated aid should interactively
support effective and timely decision making by the human.
We present a domain-independent categorization of the types of alerts a
plan-based monitoring system might issue to a user, where each type generally requires different monitoring techniques. We
describe a monitoring framework for integrating many domain-specific and
task-specific monitoring techniques and then using the concept of {value of an alert} to avoid operator overload.

We use this framework to describe an execution monitoring approach we have
used to implement Execution Assistants (EAs) in two different dynamic,
data-rich, real-world domains to assist a human in monitoring team behavior.
One domain (Army small unit operations) has hundreds of mobile,
geographically distributed agents, a combination of humans, robots, and
vehicles. The other domain (teams of unmanned ground and air vehicles) has a
handful of cooperating robots. Both domains involve unpredictable
adversaries in the vicinity. Our approach customizes monitoring behavior for
each specific task, plan, and situation, as well as for user preferences.
Our EAs alert the human controller when reported events threaten plan
execution or physically threaten team members. Alerts were generated in a
timely manner without inundating the user with too many alerts
(less than 10% of alerts are unwanted, as judged by domain experts).

Electronic Copies

Associated Projects

We developed a planning and decision aid (PDA) for the DARPA Small Unit Operations (SUO) program, to show the
feasibility of using advanced planning technologies in SUO. The PDA monitors the execution of
machine-understandable plans, using events as they are realistically reported in the
battlespace, and alerts the user when the situation requires his attention.